Urban information is a kind of multi-sources data, and the variety of these data demands that we should set up an
information system. One of the major tasks is to store massive spatial data and non-spatial data and manage these data
effectively. One of the other major tasks of urbanization integration is how to search for spatial data and non-spatial data
what we need into massive information, so we need to establish indexes for spatial data and non-spatial data and construct
the relation between the two kinds of data in order to convenient query. The paper is focused on data indexes
construction, classified indexes for non-spatial data, R-trees index for spatial data and puts forward an area hiberarchy
index tree to build up direct relationship between spatial data and non-spatial data for seamless queries, and the
experiment shows that the hiberarchy index tree is much validated and something useful is obtained.
In order to construct a 3D model of object lacking of texture, the main difficulty for registration is the lacking of feature
points and the obtaining of the points' coordinates. The method handles registration problem based on the Iterative
Closed Point (ICP) algorithm, which requires only the procedure to find the closed point on a geometric entity to a given
point. The ICP algorithm is a popular method for the registration, when there is lack of feature points. In order to
compute the points' coordinates, the projector can provide the clear and stable texture on the surface of the object
lacking of texture easily. The camera is used to take photos as the image data for the next processing. Using curve
detection and space intersection, spatial points on the surface of the sheet metal parts are obtained. Sub-Models
overlapping each other are registered by ICP, so the 3D reconstruction is finished. The feasibility of ICP is verified by
the results of the experimentation.
Water body information is very important for urban planning and environment improving. Extracting water body
information from the satellite images such as MODIS images, Spot images, Radarsat SAR images and LANDSAT TM
images has been explored by some researchers. However, extracting water body information from high resolution
satellite images is still a problem because of the shade effect of buildings in urban area. The color of the calm water
surface is similar to the shadows and it is difficult to distinguish between water body and shadows from satellite
imagery. With Near-Infrared Spectral Analysis of IKONOS imagery, we present a new method to extract water body and
make distinctions between the water body and the shadows. We employ existing knowledge for extracting water body
information by image analysis at first, then the dark objects is extracted by a object-oriented operation from the high
resolution satellite image. Near-infrared spectral analysis is developed to remove the building shadows from the dark
objects extracted. Two NIR indexes are combined to remove the shadows. The experiments show that the main water
body, such as artificial lake and rivers can be extracted effectively from IKONOS imagery with the method presented in
this paper.
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